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The impact of artificial intelligence on critical thinking and clinical reasoning in health professions education: A systematic review and meta-analysis.

BACKGROUND: Critical thinking and clinical reasoning underpin healthcare professionals' ability to navigate uncertainties and deliver safe and effective care. With artificial intelligence (AI) advancement and growing adoption, AI-based educational tools are increasingly used to support these cognitive competencies' development. OBJECTIVE: To synthesize randomised and controlled clinical trials on AI-based educational tools in health professions education and examine their effects on critical thinking and clinical reasoning among health professions students. METHODS: Six electronic databases were searched from January 1, 2014 to July 28, 2025 was reviewed: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, Embase and Web of Science. Two independent reviewers performed data extraction and quality assessment using standardized JBI checklists. The GRADE approach was used to assess the certainty of evidence. Studies were pooled via random-effects meta-analyses or narrative syntheses. RESULTS: Fourteen randomised controlled trials and seven controlled clinical trials were included (n = 21). Meta-analyses revealed small to medium effect sizes for the surrogate clinical reasoning outcomes of performance-based assessment scores (SMD 0.68; 95% CI [0.38, 0.98], p-value = 0.00; I2 = 38%) and knowledge test scores (SMD 0.39; 95% CI [0.09, 0.69], p-value = 0.01; I2 = 79%). Critical thinking and clinical reasoning skills and dispositions were narratively synthesized, with majority of included studies favouring AI-based interventions but the evidence had low to very low certainty. CONCLUSION: AI-based educational interventions may improve critical thinking and clinical reasoning among health profession students, but the evidence is very uncertain. This review offers preliminary insights but does not allow identification of optimal interventions or discipline-specific recommendations due to small sample sizes and substantial intervention heterogeneity. Further research is required to draw definitive conclusions. PROTOCOL REGISTRATION: CRD42025634074.

Humans

Whole genome sequencing of unusual Hepatitis C virus subtypes and drug resistance analysis during direct-acting antiviral therapy in India.

INTRODUCTION AND OBJECTIVES: Pangenotypic direct-acting antivirals (DAA) are effective against highly prevalent Hepatitis C virus (HCV) subtypes, but have been clinically validated almost exclusively in high-income countries. Unusual HCV subtypes may carry natural polymorphisms, potentially impacting DAA susceptibility. We conducted full-genome characterization and resistance analysis of unusual HCV subtypes in patients receiving DAA treatment. PATIENTS AND METHODS: In this prospective hospital-based study, eligible patients were screened for anti-HCV antibodies and active infection was confirmed by diagnostic 5'NCR-based HCV RNA detection. Genotyping was performed by core region sequencing, and viral load quantified by real-time PCR. For whole genome sequencing, multiplex primers were designed using alignments of global reference sequences. Sequencing was carried out using the Oxford Nanopore Technology platform. Phylogenetic analysis used multiple sequence alignment and the HCV-GLUE resource for resistance-associated substitution (RAS) analysis. RESULTS: Predominant genotype was genotype 3 in 64.3% (n = 45); genotype 6 in 21.4% (n = 15); and genotype 1 in 14.2% (n = 10). Unusual HCV subtype 6xa was detected in two patients and showed no NS5A resistance mutations. One genotype 3b patient relapsed at 24 weeks post-DAA treatment completion and carried NS5A resistance-associated substitutions 30 K and 31 M both at baseline and at relapse, conferring high-level resistance to NS5A inhibitors. CONCLUSION: This is the first report from India of whole genome sequencing of HCV subtype 6xa. The identification of NS5A resistance mutations in the 3b relapse case underscores challenges for global HCV elimination strategies.

Humans

Prevalence of POMC allele associated with obesity in feline population in Vietnam.

Feline obesity is an increasingly important health problem influenced by both genetic predisposition and husbandry practices. This study investigated the prevalence and phenotypic relevance of the feline proopiomelanocortin (POMC) c.28G > C (p.Gly10Arg) variant in a Vietnamese cat population and evaluated environmental factors associated with obesity. A total of 63 clinically healthy cats were classified as normal weight (body condition score [BCS] 5-6/9; n = 40) or obese (BCS ≥7/9; n = 23). Genotyping was performed using a newly developed PCR-restriction fragment length polymorphism assay and validated by Sanger sequencing. Ventral subcutaneous adipose tissue (VSAT) thickness was measured ultrasonographically as an objective indicator of adiposity. Genotyping revealed a high prevalence of the risk-associated C allele, with 45/63 cats (71.4%) carrying the GC genotype and 18/63 (28.6%) carrying the CC genotype, whereas the GG genotype was not detected, giving a Callele frequency of 64.3%. Obese cats had significantly greater body weight and VSAT thickness than normal-weight cats. Neuter status and ad libitum feeding were significantly associated with obesity, whereas diet type, housing, exercise frequency, and begging behavior were not. Although genotype distribution did not differ significantly between normal and obese cohorts, obese CC cats showed significantly greater VSAT thickness than obese GC cats, indicating an allele-dosage effect on adiposity. These findings suggest that the POMC c.28G > C variant is a useful risk-informative marker and that combining genetic screening with objective fat assessment may support earlier identification and prevention of feline obesity in Vietnam under routine laboratory conditions and guide personalized management strategies in practice.

Animals

Phytolacca acinosa Roxb. induces intestinal toxicity through the histamine-MLCK-tight junction axis: Integrated evidence from proteomics, metabolomics, intestinal organoids and epithelial barrier validation.

Phytolacca acinosa Roxb. (PR) is a saponin-rich medicinal plant associated with gastrointestinal toxicity, but the mechanisms underlying PR-induced intestinal barrier injury remain unclear. In this study, raw PR extract was analytically characterized by UPLC-ZenoTOF-MS/MS, confirming triterpenoid saponins as the predominant constituents. C57BL/6 J mice were orally exposed to characterized PR extract (1.20 or 12.0 g/kg for 5 h), and Caco-2 cells and mouse intestinal organoids were used to assess epithelial toxicity and barrier disruption. Histopathology, ELISA, FITC-dextran permeability assays, immunofluorescence, CCK-8, LDH release, western blotting, DIA-based proteomics and untargeted metabolomics were integrated to define toxicological mechanisms. PR induced dose-dependent intestinal inflammation and barrier dysfunction, with the ileum as the most sensitive target. PR increased serum DAO and D-lactate and intestinal TNF-α and IL-1β, disrupted organoid morphology, enhanced epithelial permeability, and reduced ZO-1 expression. Proteomics revealed changes in inflammatory, lipid-metabolic, cytoskeletal and tight-junction pathways, including upregulation of MLCK3 and phospholipase-related proteins and downregulation of ZO-1 and ZO-2. Metabolomics identified histidine metabolism disturbance and histamine accumulation. Integrated multi-omics and pharmacological validation indicated that histamine activated the PLC/IP₃/Ca²⁺/CaM/MLCK cascade, promoting MLC phosphorylation, tight-junction disassembly and epithelial leakiness. MLCK inhibition partially restored ZO-1/ZO-2 expression and attenuated PR-induced epithelial injury. These findings identify the histamine-MLCK-tight junction axis as a key mechanism of PR-induced intestinal toxicity and support hazard identification of saponin-rich PR exposure.

Animals

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans

Self-Report Health Screening Tools in Female Athletes: A Systematic Review of Domain Coverage, Validation, and Use Across Participation Levels.

BACKGROUND: Female athlete health encompasses multiple interconnected domains; however, the self-report screening tools used to assess these domains have not been comprehensively synthesised. OBJECTIVE: To systematically identify self-report health screening tools used to assess female athlete health, map domain coverage, determine validation reporting, and describe application across participation levels. METHODS: This systematic review was pre-registered with PROSPERO ( CRD420251056910 ) and conducted in accordance with PRISMA guidelines. Four databases (PubMed, MEDLINE, SPORTDiscus and Web of Science) were searched from inception to January 2026 using female health and screening-related terms. Methodological quality was appraised using Joanna Briggs Institute and National Institutes of Health tools, and findings were synthesised descriptively. Eligible, peer-reviewed studies reported the use, development or validation of self-report health screening tools assessing one or more domains relevant to female health applied in female athlete populations, spanning recreational through elite participation levels. All sports and activities were included. The search was restricted to English language with no date limits. RESULTS: In total, 360 studies (1990-2026) representing 134,506 female participants spanning recreational to elite sport and 273 screening tools were included. Mental health (n = 77, 34.1%), disordered eating (n = 33, 14.6%) and body image (n = 30, 13.3%) predominated. Domains related to female health, including menstrual health, pelvic floor health, pregnancy/postpartum and breast health were comparatively underrepresented. Most studies reported tools were used for risk identification (n = 323, 80.3%). Validation reporting was inconsistent, with half (n = 180, 50%) reporting use of at least one validated tool. Tool use was concentrated in professional and elite sport, with limited inclusion of recreational, masters and disability athlete cohorts. Health literacy constructs were explicitly assessed in 12.5% of studies (n = 45). CONCLUSIONS: Health screening in female athlete populations remains fragmented and uneven in domain coverage, with inconsistent validation reporting. Development of integrated, multi-domain and contextually inclusive screening frameworks is warranted.

Journal Article

Co-location of services: an umbrella review to consider how primary care estates could be better used to support disadvantaged groups.

AIM: To examine how co-located community and health services in primary care could support disadvantaged groups. BACKGROUND: Co-locating services is thought to improve access, collaboration, and patient outcomes. There are thousands of primary care premises across the UK. At a time of stagnating or widening health inequalities, they present an ideal opportunity to support communities, especially in disadvantaged areas. METHOD: We conducted a systematic umbrella review. Articles were retrieved from Ovid MEDLINE and Ovid Embase with supplementary snowball and grey literature searches. Reviews of co-located services supporting disadvantaged groups in primary care between 2010 and February 2024 were included. Quality and risk of bias were assessed using the Joanna Briggs Institute checklist. Two reviewers assessed eligibility, extracted data and assessed quality. Outcomes relating to health, welfare, healthcare utilization, and activity and processes were assessed. Data were narratively synthesized using a convergent integrated approach. FINDINGS: 2626 studies were screened, supplemented by snowball and grey literatures searches. Thirteen reviews were included for synthesis. One review included meta-analysis. Three models of care were identified; legal advice, welfare advice, and complementary health care. Data were synthesized according to themes: access and engagement, quality of care, efficiency, improved health, and improved social factors. We found co-located services can improve access to care, engagement in treatment, and quality of care for disadvantaged groups. Improvements to social determinants of health and mental health and well-being outcomes were reported. Findings were inconsistent when considering the impact of co-location on efficiency. We conclude that co-located services in primary care have the potential to improve identification of people most in need and improve their access to high quality health care and social support. Policy makers and practitioners should maximize the use of primary care estates to support disadvantaged groups and communities.

Humans

Retrosigmoid craniotomy surgical guide: The way forward for precise exposure of the transverse-sigmoid sinuses.

INTRODUCTION: The retrosigmoid craniotomy is the workhorse approach to the cerebellopontine angle. Accurate localisation of the transverse-sigmoid junction (TSJ) is key for optimised exposure and cerebellar retraction. Various methods, both anatomical and navigational, have been used but with suboptimal results. We utilised a 3D-printed retrosigmoid surgical guide in an attempt to overcome this and report our early outcomes and experiences in the design, production and utilisation of the guide. METHODS: This is a prospective cohort study of the patients with retrosigmoid craniotomies performed using the surgical guides. Patient demographics and diagnoses, along with the accuracy of the planned burrhole and craniotomy, need for craniotomy extension, presence of venous sinus injury, set-up time, and cost were reported. RESULTS: There were ten cerebellopontine angle cases in which the surgical guides were utilised, three petrous meningiomas, two trigeminal neuralgias, two metastasis, and three other tumours. The planned burrhole and craniotomy were precise in all cases with accurate exposure of the TSJ and no requirement for craniotomy extension. The mean set up time was 3.9 min, and the mean cost of the surgical guides was USD 470.90. One elderly patient had an intraoperative transverse sinus injury related to adherent dura that was planned for exposure. CONCLUSION: The 3D-printed surgical guide is a potential solution to the rapid, precise and consistent identification of the TSJ when performing a retrosigmoid craniotomy. We present our early experience and discuss nuances in the designing, production, and intraoperative phases to optimise the precision of this guide. We suggest two methods to avoid sinus injury in elderly patients: either to plan the craniotomy to the edge of the sinus, or to plan sinus exposure but to use burr drills rather than the osteotome, as in our case, to expose the sinus.

Humans

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans

A child and young person focused systematic review of scrotal ultrasound with Mitigants to identify missed torsion.

BACKGROUND: Diagnostic accuracy of ultrasound for adults is stated as excellent. Paediatric and adult acute scrotal diseases are different. Findings in adults may not apply in children. The authors have seen overconfidence and interpretation with adult disease in mind in children with scrotal pain and have seen testicular loss as a result. OBJECTIVES: To interrogate the literature methodologically to report diagnostic accuracy of ultrasound (US) for the acute scrotum specifically in CYP with a follow-up methodology which allows identification of missed torsion. STUDY DESIGN: We performed systematic review and meta-analysis of studies reporting true diagnostic accuracy of ultrasound for testicular torsion (TT). PubMed, MEDLINE, Scopus, and Web of Science databases were searched from platform start until September 2023 using MeSH terms with protocol as detailed on PROSPERO. Multiple author search was undertaken. Two authors extracted data for included studies. Study quality was reported through QUADAS-2 methodology. Surgical findings or 12 months follow up in non-operative cases would be the gold standard to identify late atrophy due to missed torsion. Studies with methodology to identify missed torsion outwith the initial consult were included for meta-analysis. RESULTS: A total of 6790 cases were reported from the 38 papers identified. Studies were often flawed with poor definition of outcomes and short follow-up duration. Meta-analysis of the 10 high-quality studies revealed pooled sensitivity and specificity of 0.93 and 0.99. Doppler US by trained individuals demonstrated excellent diagnostic accuracy. Nonetheless, on extrapolation of the data, especially where flow was preserved, 5.6% of torsions were missed. DISCUSSION/CONCLUSION: Our review confirms a high diagnostic accuracy of US for TT in CYP. However, a 5.6% missed torsion rate was found if flow alone was considered diagnostic. The authors suggest US should be used as an adjunct in ambiguous cases, ensuring that clinically obvious torsion goes to theatre immediately and is not delayed by ultrasound. TRIAL REGISTRATION: PROSPERO: CRD42023412619.

Humans

Serotypic and Genomic Diversity of Vibrio anguillarum in Rainbow Trout Farms in Turkey: Implications for Vibriosis Control and Vaccine Candidate Selection.

Outbreaks of vibriosis caused by Vibrio anguillarum are a persistent constraint on rainbow trout (Oncorhynchus mykiss) aquaculture. However, information on the population structure of field strains in Turkey has been lacking. Here, we report the first systematic serotypic, proteomic, and genomic characterization of 23 V. anguillarum isolates collected over 10&#x2009;years from rainbow trout farms located in six major aquaculture regions of Turkey. Serological analyses based on microagglutination, supported by ELISA characterization of hyperimmune sera, identified a clear predominance of serotype O1, whereas isolate V12 exhibited a non-agglutinating, atypical O-antigen profile. Protein profiling (SDS-PAGE) and immunoblotting showed largely conserved whole-cell protein patterns among the isolates, but distinct immunogenic bands at 14, 18, and 40&#x2009;kDa were detected in isolates V18 and V21. Long-read whole-genome sequencing revealed that most Turkish isolates grouped within the global O1 clade, while V12, V25, and V28 isolates occupied more distant branches. Comparative genomics demonstrated a conserved core virulence gene set (RTX toxins, siderophore and iron-uptake systems, motility and adhesion factors, Type VI secretion system), with strain-dependent variation in accessory loci such as anguibactin and T6SS-I. Experimental infections of rainbow trout demonstrated significant differences in virulence among isolates (p&#x2009;<&#x2009;0.05), with the V18 isolate showing high, the V15 intermediate, and the V12 low-mortality rates. By elucidating the relationship among the serotype, immunogenic protein profiles, virulence gene repertoires, and in&#xa0;vivo pathogenicity, this study provides a comprehensive overview of the antigenic and genomic diversity of Vibrio anguillarum isolates from Turkey. Notably, the identification of V18 and V21 as promising candidate strains for further vaccine evaluation, characterized by high virulence and unique immunogenic features, provides a scientific foundation for the development of serotype-specific vaccination strategies to mitigate vibriosis-associated losses in aquaculture.

Animals

Externally validated risk prediction models for gestational diabetes mellitus: A systematic review and meta-analysis.

INTRODUCTION: Risk prediction models for gestational diabetes mellitus (GDM) offer potential for early identification and targeted prevention. External validation is crucial to assess model performance across diverse populations. Despite the availability of numerous GDM prediction models, limited evidence exists on their external validation frequency, methodological quality, and clinical applicability. This systematic review evaluated externally validated GDM prediction models, focusing on methodological rigor, reporting standards, and clinical relevance to inform future research and implementation. MATERIAL AND METHODS: Databases including Ovid MEDLINE, Embase, Scopus, Emcare, and CINAHL were searched up to May 1, 2025. Studies reporting external validation of GDM risk prediction models were included. Two reviewers independently screened studies. Data were extracted using the CHARMS framework, and risk of bias and applicability were assessed using PROBAST+AI. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125758). RESULTS: Twenty-six studies validated 33 models, with validation sample sizes ranging from 50 to 75&#x2009;161. Over half used the IADPSG criteria to define GDM. Discrimination metrics were commonly reported, but calibration, overall performance, and clinical utility were often lacking. Meta-analysis was feasible for only four models: Teede et&#xa0;al., Nanda et&#xa0;al., Naylor et&#xa0;al., and Van Leeuwen et&#xa0;al., each showing fair discrimination. The Teede et&#xa0;al. model was the most widely validated, with 11 external validations across six continents and a pooled AUC of 0.72 (95% CI: 0.67-0.76). Despite fewer validations, the Nanda et&#xa0;al. model achieved the highest pooled discrimination (5 validations; pooled AUC 0.77, 95% CI: 0.74-0.80). The Naylor et&#xa0;al. and van Leeuwen et&#xa0;al. models also underwent meta-analysis, as sufficient external validation studies were available to support comparative performance assessment. Notably, 69.23% of studies had a high risk of bias. CONCLUSIONS: While many models showed acceptable predictive performance, most validations were methodologically weak. Future studies should follow best-practice guidelines and promote scalable validation strategies, such as algorithm sharing, to enhance clinical utility.

Humans

Paediatric penile length: a systematic review and meta-analysis.

OBJECTIVE: To assess geographical variation in stretched penile length among prepubertal boys and evaluate temporal trends over the past two decades, as defining reference values for genital organ size remains crucial for early identification of development disorders. METHODS: The PubMed, Cochrane and Scopus databases (no deadlines for publishing were imposed) were searched according to the Preferred Reporting Items for Systematic Review and Meta-analyses statement. Five authors independently extracted individual participant data and assessed the risk of bias. Studies with quantitative penile lengths were included; those involving congenital malformations were excluded. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (registration number CRD42022335643). RESULTS: A total of 55 studies from 2000 to 2024 were evaluated, including data from 31&#x2009;915 boys. Pooled mean stretched penile length estimates were 3.07&#x2009;cm (95% confidence interval [CI] 2.88-3.26&#x2009;cm) for the 1-week-old boys, 3.73&#x2009;cm (95% CI 3.53-3.93&#x2009;cm) for the 1-year-old boys, 4.69&#x2009;cm (95% CI 4.49-4.88&#x2009;cm) for the 2-5&#x2009;year-old boys, and 5.43&#x2009;cm (95% CI 5.20-5.66&#x2009;cm) for the 5-10&#x2009;year- old boys. When comparing data from the 2000s to the 2020s, stretched penile length decreased by 16.2% (from 3.46 to 2.90&#x2009;cm), 16.3% (from 4.17 to 3.49&#x2009;cm), 21.5% (from 5.31 to 4.17) and 26.2% (from 6.46 to 4.77&#x2009;cm) in the 1-week-old, 1-year-old, 2-5-year-old and 5-10-year-old boys, respectively. Subgroup analysis for those aged >2&#x2009;years showed significant variations by geographical region (P&#x2009;<&#x2009;0.001). CONCLUSIONS: The present study observed large variations in penile length across geographical regions and among prepubescent boys of different ages, while also suggesting a possible decline over the past two decades.

Humans

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25&#xa0;years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n&#x2009;=&#x2009;10, 62.5%), language (n&#x2009;=&#x2009;2, 12.5%), gait (n&#x2009;=&#x2009;2, 12.5%), caregiver proximity (n&#x2009;=&#x2009;1, 6.3%), EEG power (n = 1, 6.3%),&#xa0;and arousal (n&#x2009;=&#x2009;1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps,&#xa0;and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n&#xa0;=&#xa0;5), support vector machines (n&#xa0;=&#xa0;4), k-nearest neighbor (n&#xa0;=&#xa0;3), decision trees (n&#xa0;=&#xa0;3), random forests (n&#xa0;=&#xa0;5), neural networks (n&#xa0;=&#xa0;2), linear discriminant analysis (n&#xa0;=&#xa0;1), and pre-trained CNNs (n&#xa0;=&#xa0;1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n&#xa0;=&#xa0;12 to n&#xa0;=&#xa0;39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans

Genomic insights into end-use grain quality and nutritional traits of an ancient Indian dwarf wheat ( Triticum sphaerococcum Percival) population using a multi-locus genome-wide association study.

BACKGROUND: Triticum sphaerococcum, an ancient hexaploid wheat species, is renowned for its stress resilience and superior nutritional quality. A panel of 116&#x2009;T. sphaerococcum accessions (the largest known collection at a single site globally), with six bread wheat released varieties, was evaluated for its potential for genetic quality improvement. Field experiments were conducted under standard, heat and moisture-deficit conditions across two cropping seasons for ten grain end-use quality and nutritional traits. RESULTS: Genotypes showed highly significant differences (P&#x2009;&#x2264;&#x2009;0.001) for measured traits, with high broad-sense heritability resulting from substantial genotypic variance contributions. Triticum sphaerococcum consistently outperformed T. aestivum across environments, with moisture-deficit stress proving more detrimental to quality parameters than heat stress, while micronutrient content increased under stressed conditions. Trait correlations revealed that the gluten index (GI) correlated negatively with the grain hardness index (GHI), wet gluten (WG), and water-binding capacity (WB), while positively correlating with dry gluten (DG) and protein content (PRO), whereas grain iron (GFE), zinc (GZN), and protein showed consistent positive interrelationships. Two superior accessions, PAUTS10 (WG 35.13%, DG 13.71%, PRO 16.42%, GZN 50.89&#x2009;ppm) and Sonamoti (WG 33.33%, DG 12.92%, PRO 16.27%, GZN 56.03&#x2009;ppm), were identified, surpassing the best check variety HD3226 for quality and nutritional parameters. Multi-locus genome-wide association studies identified 30 stable quantitative trait nucleotides across environments, with candidate gene analysis revealing genes involved in transcription regulation, biosynthetic processes, metal ion homeostasis, and transport. CONCLUSIONS: Triticum sphaerococcum demonstrated superior grain quality and micronutrient potential compared with modern wheat, highlighting its value as a genetic resource for biofortification. The identification of elite accessions and stable quantitative trait nucleotides (QTNs) provides useful targets for breeding programs aimed at improving protein and micronutrient content. Integrating ancient germplasm with modern genomic tools can accelerate the development of nutritionally enhanced wheat varieties. &#xa9; 2026 Society of Chemical Industry.

Triticum

Use of indocyanine green fluorescence versus patent blue V dye for sentinel lymph node biopsy in early breast cancer, a randomized controlled trial.

BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard for axillary staging in early breast cancer. While the combination of radioisotope and blue dye (e.g., patent blue V, PBV) remains the standard, it has limitations including logistics, variable identification rate (IR), and allergic potential. Indocyanine green (ICG) fluorescence is a promising alternative, but high-quality comparative evidence is needed. METHODS: This was a single-center, prospective, randomized controlled trial. Forty patients with early-stage, node-negative breast cancer were allocated to SLNB using either ICG (n&#x2009;=&#x2009;20) or PBV (n&#x2009;=&#x2009;20). All patients subsequently underwent completion level I-II axillary lymph node dissection (ALND) as the pathological reference standard for diagnostic performance assessment. Primary outcome was sentinel lymph node (SLN) IR. Secondary outcomes included detection time, number of SLNs retrieved, false-negative rate (FNR), and safety. RESULTS: Baseline characteristics were comparable between groups. The SLN IR was significantly higher with ICG (100% [20/20]) than with PBV (75% [15/20], p&#x2009;=&#x2009;0.047). ICG was associated with a significantly shorter median detection time (14.5 vs. 24.0&#xa0;min, p&#x2009;<&#x2009;0.001) and retrieved more SLNs (mean: 3.6 vs. 2.4, p&#x2009;=&#x2009;0.002). Most critically, ICG demonstrated 100% sensitivity, specificity, negative predictive value (NPV), and overall diagnostic accuracy, with a 0% FNR. In contrast, PBV achieved a sensitivity of 75%, an overall diagnostic accuracy of 90%, and an FNR of 25%. No ICG-related adverse events occurred. PBV caused skin discoloration in 75% of patients and one (5%) allergic reaction. CONCLUSION: ICG fluorescence achieved a higher SLN IR, shorter detection time, higher sensitivity, lower FNR, and fewer tracer-related adverse events than PBV as a single tracer for SLNB in patients with early-stage breast cancer. These findings suggest that ICG is a promising standalone tracer when radioisotope mapping is unavailable. Larger multicenter studies are required before widespread adoption can be recommended.

Humans